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A Multispectral Bidirectional Reflectance Distribution Function Study of Human Skin for Improved Dismount Detection
| Content Provider | Semantic Scholar |
|---|---|
| Author | Koch, Bradley M. |
| Copyright Year | 2012 |
| Abstract | The war on terrorism has brought with it many challenges, one of which being combatants wearing no standard uniform and blending into the urban population. To assist with enemy detection and tracking, imaging systems that acquire spectral information bring to light many features in a scene which were once undetectable. Our research utilizes multispectral technology to better exploit naturally occurring phenomena to identify combatants. In 2008, the Sensors Exploitation Research Group at the Air Force Institute of Technology began using spectral properties of skin for the detection and classification of humans. Since then, a multispectral skin detection system was developed to exploit the optical properties of human skin at wavelengths in the visible and near infrared region of the electromagnetic spectrum. A rules-based detector, analyzing an image spectrally, currently bases its skin pixel selection criteria on a diffuse skin reflectance model. However, when observing skin in direct view of the sun, a glint of light off skin is common and indicates specularity. The areas of skin with a high degree of specular reflectance result in misdetections. We show that skin is characterized by diffuse and specular reflectance, with both components dependent on the scene configuration. While we cannot always rely on the person to directly face the camera or have constant illumination conditions, it is important to have flexibility with the rules-based detector as the scene changes. Our research better characterizes skin reflectance as a function of source and detector angular locations to improve on the rules-based detector. Our research approach first characterizes skin's specular reflectance with direct measurements. The fitting of a bidirectional reflectance distribution function model to iv the measurements with approximately 8.2% error allows us to incorporate the specular reflection component into the existing diffuse model. A method for extracting surface reflectance of a digitized three dimensional subject, paves the way for simulating many different conditions for a representative detection scenario. The result is a method to model the effects that changing scene configuration has on skin reflection and our ability to reliably do skin detection. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://scholar.afit.edu/cgi/viewcontent.cgi?article=2406&context=etd |
| Alternate Webpage(s) | https://apps.dtic.mil/dtic/tr/fulltext/u2/a540185.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
